User concerns and satisfaction drivers in Chinese nursing homes: insights from online review data

BACKGROUND: By 2024, 23% of China's population was aged 60 and above, with more than 2.3 million older adults residing in nursing homes. Understanding how service users evaluate nursing homes and the factors influencing their satisfaction can provide actionable recommendations for policymakers and nursing home managers. This helps better align care provision with the needs and expectations of older adults and their families. METHODS: Utilizing data from Dianping.com, this study employed BERTopic for overall topic modeling, alongside LDA to compare variations in user concerns across different identities and different city tiers. Furthermore, multivariate regression and random forest models were integrated to identify the factors driving user satisfaction. RESULTS: We analyzed 14,525 nursing home user reviews and identified four primary themes and twenty secondary themes of user concerns. Regression analysis and random forest modeling revealed that "Staff Attitude" and "Atmosphere" were the factors most strongly associated with user satisfaction. Thematic attention varies by user identity: prospective users prioritize physical infrastructure, relatives focus on clinical care, and actual residents emphasize daily activities. Furthermore, users in second- and third-tier cities express higher satisfaction than their counterparts in first-tier cities. CONCLUSIONS: This study identifies staff attitude and atmosphere as important factors influencing satisfaction in Chinese nursing homes, with user concerns varying by identity and city tier. Nursing home operators should prioritize staff training to foster a warm living atmosphere, while policymakers should build user-centered evaluation systems and implement targeted regulation. Promoting personalized care for older adults nationwide will ultimately improve satisfaction with institutional care.